R/rbenchmark.R

In rportfolios: Random Portfolio Generation

rbenchmark <- function( m, n=2, k=n, segments=NULL, x.t=1,
    margins=c( "unif", "beta", "exp",    "frechet", "gamma",
               "gev",  "gpd",  "gumbel", "lnorm",   "logis",
               "norm", "weibull"), ... )
{
###
### This function generates m long only random portfolios with n investments where
### weights are between given lower and upper bound and the sum of
### the weights equals a given total sum.  Results are return as a matrix
###
### Arguments
### m = a positive integer value for the number of portfolios to be generated
### n = a positive integer value for the number of investments in a portfolio
### k = a positive integer value for the number of non zero weights
### segments = a list or vector of investment indices that define portfolio segments
### x.t = a numeric value for the sum of the investment weights
### margins = a character value for the marginal distribution of the truncated variates
### ... = additional arguments passed to the random variable function for the margin
###
    if ( missing( m ) )
        stop( "Argument 'm' is missing" )
    if ( m <= 0 )
        stop( "Argument 'm' is not positive" )
###
### private function
###
    by.case <- function( case, number, size, theseSegments, total, marginals, ...)
    {
        return( random.benchmark( n=number, k=size, segments=theseSegments, x.t=total, 
            margins=marginals, ... ) )
    }
    weights <- t( sapply( 1:m, by.case, n, k, segments, x.t, margins, ... ) )
    if ( n == 1 ) {
        weights <- t( weights )
    }    
    return( weights )
}